Image and video resizing involves adapting an image or video to displays with different sizes and aspect ratios relative to the original image/video size, resulting in warping or distortion. Recently, a significant amount of effort has been devoted to this problem. Video retargeting addresses the problem of adapting a video for display at different size and aspect ratios than originally intended.
While various video and image processing approaches have experienced some success, images generated have often included undesirable characteristics. For example, many images generated using previous approaches sacrifice temporal coherence, resulting in jitter, or require expensive space-time optimization. One such approach involves seam carving, which changes image sizes by removing or inserting seams in regions that are least noticeable, to retain as much information as possible while avoiding objectionable distortion. Another approach involves a spatially varying warp application in which distortion is distributed to regions that are less salient to the human visual system than the others. While some resizing approaches such as content-aware approaches, seam carving-based methods and spatially varying warp-based methods can be useful for image resizing, their extension to video has been challenging. Moreover, various processes used to generate such images require significant computational resources and are often unsuccessful for videos with significant camera and object motion. Many approaches that address camera and object motion involve intense computation.
These and other problems have been challenging to a variety of methods, devices and systems that use or benefit from video resizing.